XGBoost: A Scalable Tree Boosting System

Tianqi Chen and Carlos Guestrin submitted XGBoost: A Scalable Tree Boosting System to arXiv on March 9, 2016. The paper describes XGBoost as a scalable end-to-end tree boosting system and presents a sparsity-aware algorithm, a weighted quantile sketch for approximate tree learning, and systems techniques for scaling beyond billions of examples.